Edge Artificial Intelligence for Electrical Anomaly Detection Based on Process-In-Memory Chip

Abstract

Neural-networks (NNs) for the current feature analysis bring novel electrical safety functions in smart circuit breakers (CBs), especially for preventing the fire hazard from electric vehicle/bike battery charging. In this work, the edge artificial intelligence (AI) solutions for the electrical anomaly detection were designed and demonstrated based on the process-in-memory (PIM) AI chip. The ultra-low power and high-performance character of PIM AI chips enable the edge solution to embed in the limited space inside the circuit breaker and to detect improper battery charging at millisecond latency.